Two Ideas for a Better Visualization Web

There is a reasonable amount of information about visualization available on the web. There are still huge gaps though, especially when it comes to bridging the gap between academic research and the rest of the world, though. Here are two ideas: one simple, one rather involved.

Ben Shneiderman has recently been talking to a number of people about a resources collection for visualization similar to KDD Nuggets. I'm skeptical about the need for such a thing. Lists of resources need to be kept up to date, and they can lose their utility quite quickly when they go for completeness rather than usefulness (Andy Kirk's list of everything ever is a good example).

This had me thinking about better formats, though. How can we make information more accessible? How can we make research results available and interesting to people? And how can we drag more of research out onto the web?

The Paper Explainer

Papers are what academics publish. But they are often quite terse, and are usually written in a mad rush to beat a deadline. Going back to a paper from a few years ago can be painful: typos, tortured writing, and some really interesting points were buried rather than made the center of the paper.

Carlos Scheidegger thought about this recently too:

Lately I've become tempted to rewrite some of my recent papers into webpages that actually -- and slowly -- explain everything in it. (1/n)

The posting I recently did to walk through the pie chart study results was along similar lines: find a better way to explain the results in a way that I now feel is much clearer and helpful than the paper (it's also glossing over many details, admittedly, but otherwise it would have gotten out of hand).

What Carlos is suggesting would be tremendously useful, both for people interested and wanting to read about published ideas in more depth and for the author of the paper. I learned quite a bit when looking through the results again and thought about how I would explain them to an audience that doesn't know what a confidence interval is.

It's a lot of work, for sure. I probably wouldn't have done this if I hadn't created the charts for my Information+ talk. Even so, just writing it all up took a while. But now a lot of people are reading about the work Drew Skau and I did. It's actually reaching people. Far, far fewer people are ever going to bother reading the papers.

If you're an academic who has considered blogging, the paper explainer is the ideal starting point. Grab a few of your papers and start writing! Maybe you have some early work that you now think is funny because you were so naive. Or there's an idea you've thought about in multiple places but never quite put into words. Or just dive deeper into one paper. Even if nobody else reads it, you'll learn a lot yourself.

The VisRxiv or DataRxiv

On the other end of the spectrum is the idea of a pre-print server for data visualization. The physics community has been doing this with great success for a number of years now with arXiv. The site lets people upload papers and get feedback before submitting to a journal. It helps to get ideas out earlier and to hone a paper before it even goes into review.

Other fields have taken note. Biology just started BioRxiv, and Chemistry is now pondering their own server, ChemRxiv. Clearly, an unpronounceable name is the first requirement, but there are a few more hurdles.

Visualization by itself is probably too small to really make this work. But if this could include a number of fields like statistics and parts of psychology, it could work.

arXiv has a computer science section with an HCI subsection. That's where you'll find a handful of visualization papers. This follows the age-old tradition of visualization being ignored in classification schemes, and it clearly doesn't help get noticed or get feedback for work uploaded there.

There are lots of things a more visualization-centric site could do that arXiv doesn't: a stronger focus on images, embedded demos of techniques; interactive widgets to explore data from studies, etc. There are so many things that could be done beyond just hosting PDFs that would create more interest and engagement.

To make sense, a VisRxiv or DataRxiv would need some serious long-term support, and probably some sort of institutional backing. If the site is funded from a three-year grant, or run as a hobby by somebody, it's going to disappear or fall apart after a few years.

Still, I think it would be incredible helpful to have such a site. It would create a different kind of conversation than exists right now, and help push publishing in visualization towards a model that's a bit more forward-looking than what we have right now.

Robert Kosara is Senior Research Scientist at Tableau Software, and formerly Associate Professor of Computer Science. His research focus is the communication of data using visualization. In addition to blogging, Robert also runs and tweets. Read More…

Reader Interactions

Comments

I can’t say I’d agree that the observation you make that the visualisation resources list on my site has lost utility. Perhaps for people already established in the field it is of less value but my target audience is largely beginners/new entrants to this subject rather than, necessarily, academic/research audiences. It is admittedly hard work keeping it up-to-date (most recently I did some pruning two weeks ago after 12 months without the capacity) reflecting the evolving landscape of this field. However, that is what it aims to provide – a collection of most of the current visualisation or visualisation-related technology options out there based, roughly, on a classification of the general raison d’etre of each tool. All I can say is that feedback from visitors – and visitor numbers – suggests this is a quite useful catalogue from which they can explore new options to expand their capabilities. Curating this content further with more nuanced commentary about the relative strengths/features in each case is an entirely different proposition that I could never wish to undertake.

I knew you’d take issue with this ;) What I meant was that a long list of options without any guidance just leads me to decision fatigue. It can definitely be helpful when I’m looking to research something in depth and want to see what all the options there are. But I also appreciate a clear recommendation that says: if you want to do A, first try this, if you’re after B, try that! If that doesn’t end up working out, I can always go back to the long list and spend more time digging through all the options myself.

I love the idea of a paper explainer. As a non-academic (graphic designer by trade) in the field of data visualization, it’s possible—but painfully difficult to read most papers. I applaud any effort to make academic research more accessible to the masses.

A pleasant side-effect might even be the reduction of absurd and misleading headlines we see in the media when they decide to report on something before understanding it.